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Record W2095574503 · doi:10.1109/tvlsi.2005.848817

A novel FPGA architecture supporting wide, shallow memories

2005· article· en· W2095574503 on OpenAlexaff
Steve Oldridge, Steven J. E. Wilton

Bibliographic record

VenueIEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2005
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsField-programmable gate arrayBenchmark (surveying)Computer scienceArchitectureEmbedded systemGate arrayComputer architectureComputer hardwareParallel computingMemory architecture

Abstract

fetched live from OpenAlex

This paper investigates an architecture designed to implement wide, shallow memories on a field programmable gate array (FPGA). In the proposed architecture, existing configuration memory normally used to control the connectivity pattern of the FPGA is made user accessible. Typically, not all the switch blocks in an FPGA are used to transport signals. By adding only a modest amount of circuitry, the configuration memory in these unused switch blocks (or unused paths within used switch blocks) can be used to implement wide, shallow buffers and other similar memory structures. The size of FPGA required to implement a benchmark circuit that makes use of the wide, shallow memories, is 20% smaller than a standard memory architecture. In addition, the benchmark circuit is on average 40% faster using the proposed architecture.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.227
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2005
Admission routes1
Has abstractyes

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